SwiftKey partners with Oxford University Press in quest to find 2015’s best-loved ‘Word of the Year.
If we were to ask you which word you think has most captured the public imagination this year, which would you choose? If we were to then tell you that for the first time ever it isn’t a word at all, but a symbol, and a yellow-faced one shedding tears at that, would you be surprised?
Well, that’s exactly what has happened, and we can’t say we’re surprised! In an exciting new partnership, SwiftKey has collaborated with Oxford University Press for Oxford Dictionaries 2015 Word of the Year campaign. Only this time it won’t be a word at all, but an emoji (drumroll please) – specifically the Face with Tears of Joy .
2015 has truly been the year of the emoji; it’s increasingly becoming the most popular, universal form of communication and self-expression, seemingly evolving as a language in its own right. For that reason, OUP chose an actual emoji as their Word of the Year, reflecting the huge public appetite for these engaging and addictive ‘picture words’.
SwiftKey has already released benchmark emoji reports on how different people use emoji across the world, for which we analyzed over 1.5 billion pieces of data. We used this data analysis to find the most popular emoji for 2015* which turned out to be Face with Tears of Joy, making up almost 20% of all emoji sent over this period! Coming in a close second is Face Throwing a Kiss , and several other ‘faces’ made the top 10.
The appeal of emoji seems to lie in how personal they can make communication – the hundreds of emoji that are now available are able to be used in very different ways from person to person. They are also incredibly accessible, and anyone can use an emoji (or two) to enhance what they are saying, regardless of the language they are speaking in.
To read more from Oxford University Press, see: http://blog.oxforddictionaries.com/2015/11/word-of-the-year-2015-emoji. We’d love to hear what you think – do you agree with this result? Let us know at the hashtag #OxfordWOTY.
Sarah and the team
*Data based on a comparison analysis between Q1 2014 and Q1 2015 for En_UK and En_US.